Autonomous Vehicle Failure Feedback Linked to Time and Location
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Solution Overview
Problem
Current autonomous vehicle systems lack an efficient method to collect and analyze feedback on vehicle failure events, which are crucial for improving vehicle performance and safety.
Innovation Solution
A computing system is implemented within autonomous vehicles to detect vehicle failure events and provide an interactive user interface for human passengers to enter feedback. This feedback is associated with the time, location, and data collected during the event, enabling detailed analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If autonomous vehicle systems implement feedback collection mechanisms for failure events, then the quality and granularity of feedback data improve, but the system complexity and computational requirements increase
Solution Approach 1:
The system pre-defines multiple failure event categories (safety critical, comfort, operational) with associated feedback questions before failures occur. When a failure is detected, the system immediately presents the relevant pre-configured feedback form, eliminating the need for complex real-time question generation and reducing computational burden during critical moments.
Solution Approach 2:
The feedback collection system is segmented into distinct modules: failure detection module, categorization module, feedback form generation module, and data association module. Each module handles a specific aspect of feedback collection, making the overall system more manageable and easier to implement without requiring a monolithic complex architecture.
2Loss of information
If the system collects detailed feedback with time, location, and sensor data associations, then the analytical value of feedback increases, but the data processing and storage requirements increase
Solution Approach 1:
The system extracts only the most relevant data elements associated with each failure event (timestamp, location coordinates, selected failure category, and user feedback text). By selectively extracting only essential data points rather than storing all possible sensor data, the system maintains high analytical value while minimizing data volume and storage requirements.
Solution Approach 2:
The feedback data structure is designed to be universal and multi-functional, with standardized fields that can serve multiple analysis purposes (safety analysis, comfort optimization, operational improvement). This universal structure allows the same data to be reused across different analytical contexts without requiring separate data collection systems for each analysis type.
3Productivity
If the system provides an interactive user interface for feedback entry, then user engagement and feedback completeness improve, but the interface complexity and user burden increase
Solution Approach 1:
The user interface provides different levels of interaction complexity based on the specific failure context. For safety-critical failures, the system presents comprehensive feedback forms with multiple questions. For minor operational issues, the interface offers simpler response options. This localized adaptation of interface complexity ensures thorough feedback collection for critical events while maintaining ease of use for less severe incidents.
Solution Approach 2:
The feedback interface dynamically adapts its complexity based on the detected failure category and severity. The system adjusts the number and type of questions presented to the user in real-time, transforming from a static rigid interface to a dynamic adaptive one that optimizes both feedback quality and user effort based on the specific situation.
Data Source
AI summary
The present disclosure provides systems and methods to obtain feedback descriptive of autonomous vehicle failures. In particular, the systems and methods of the present disclosure can detect that a vehicle failure event occurred at an autonomous vehicle and, in response, provide an interactive user interface that enables a human located within the autonomous vehicle to enter feedback that describes the vehicle failure event. Thus, the systems and methods of the present disclosure can actively prompt and/or enable entry of feedback in response to a particular instance of a vehicle failure event, thereby enabling improved and streamlined collection of information about autonomous vehicle failures.